---
title: "Erica Chiang"
type: "entity"
entity_kind: "person"
status: "hub"
canonical_name: "Erica Chiang"
aliases: []
first_seen: "2026-10-12T00:00:00.000Z"
writer_model: "claude-sonnet-5"
connects_to: ["NYC high school match","recommendation-induced congestion","PiTech Initiative (Cornell Tech)","Nikhil Garg","matching markets"]
seek_code_commit: "d40ee39"
---


Cornell PhD researcher and Siegel PiTech PhD Impact Fellow who personally designed and ran the 2025-26 randomized controlled trial that nudged NYC eighth-graders toward high-performing high schools they were likely to be admitted to. First-listed author of the resulting paper on recommendation-induced congestion in capacity-constrained matching markets. Matters to this vault beyond shared co-authorship with [[entity-nikhil-garg]]: her own first-person PiTech spotlight piece describing the fall-2025 deployment ("we successfully deployed the system to about 500 eighth-grade students... as part of a randomized controlled trial") is itself a sourced primary this vault cites, giving her standing as the deployment's own author-operator, not merely a co-author on someone else's paper.

## References
- [[claim-no-independent-source-corroborates-nyc-nudge-rct-zero-rejection-result]]
- [[claim-recommendation-induced-congestion-erodes-offer-likelihood-guarantees]] · [[claim-balanced-capacitated-nudging-guarantees-safe-and-near-optimal-matches]] · [[claim-nyc-school-nudge-rct-significant-ranking-suggestive-matching-increase]]
- Capture: 10-inbox/raw/2026-10-12-does-an-independent-source-corroborate-the-nyc-school.md